A novel methodology for water-sensitive papers analysis focusing on the segmentation of overlapping droplets to better characterize deposition pattern

Abstract

Water-sensitive papers (WSPs), as an artificial target, have been generally used to evaluate spray quality in pesticide applications. Though many tools were available to analyze WSPs, they were not effective in processing the presented overlapping droplets, which prevented accurate quantification of spray quality. Here, a novel methodology was proposed to analyze WSPs, focusing on the segmentation of overlapping droplets based on concave point detection and ellipse fitting. Up to 553 WSPs obtained from field trials in apple trees were used to validate this methodology. A high overall segmentation accuracy of 77.8% was achieved for the WSPs with coverage below 25%, which allowed to precisely characterize the corresponding deposition pattern. A universal linear relationship was observed between the droplet density and coverage, independent of the sprayer and canopy characteristics. In addition, the droplet size distributions for all spray applications showed a similar trend. As the proposed methodology was not effective to segment the complex overlapping spots on the WSP with high coverage (>25%), simulated WSPs were generated to estimate the deposition pattern of high coverage based on the droplet size distribution deposited on the WSPs with low coverage. A linear relationship with a much higher slope was observed between droplet density and coverage for the high deposition, which enabled an approximate estimation of the corresponding droplet density. In general, the proposed approaches allowed to obtain more accurate spray quality indicators from the WSP collectors and could be widely used for spray application evaluation to promote precision spraying.